Spatiotemporal Adaptive Quantization for the Perceptual Video Coding of RGB 4:4:4 Data

TL;DR

This paper introduces SPAQ, a perceptual quantization method for RGB 4:4:4 video that leverages human visual system sensitivities to reduce bitrate while maintaining visual quality.

Contribution

SPAQ is a novel spatiotemporal perceptual quantization technique that adjusts quantization based on HVS spectral, spatial, and temporal masking at the coding block level.

Findings

Reduces bitrates by up to 80% compared to HEVC standard.

Achieves perceptually lossless quality as per subjective and SSIM evaluations.

Operates effectively at the coding block and prediction unit levels.

Abstract

Due to the spectral sensitivity phenomenon of the Human Visual System (HVS), the color channels of raw RGB 4:4:4 sequences contain significant psychovisual redundancies; these redundancies can be perceptually quantized. The default quantization systems in the HEVC standard are known as Uniform Reconstruction Quantization (URQ) and Rate Distortion Optimized Quantization (RDOQ); URQ and RDOQ are not perceptually optimized for the coding of RGB 4:4:4 video data. In this paper, we propose a novel spatiotemporal perceptual quantization technique named SPAQ. With application for RGB 4:4:4 video data, SPAQ exploits HVS spectral sensitivity-related color masking in addition to spatial masking and temporal masking; SPAQ operates at the Coding Block (CB) level and the Prediction Unit (PU) level. The proposed technique perceptually adjusts the Quantization Step Size (QStep) at the CB level if high variance spatial data in G, B and R CBs is detected and also if high motion vector magnitudes in PUs are detected. Compared with anchor 1 (HEVC HM 16.17 RExt), SPAQ considerably reduces bitrates with a maximum reduction of approximately 80%. The Mean Opinion Score (MOS) in the subjective evaluations, in addition to the SSIM scores, show that SPAQ successfully achieves perceptually lossless compression compared with anchors.